A Comparative Study of Kernel and Robust Canonical Correlation Analysis. - Md. Ashad Alam; Mohammed Nasser; Kenji Fukumizu (J. Multim., 2010)

Higher-Order Regularized Kernel CCA. - Md. Ashad Alam; Kenji Fukumizu (ICMLA (1), 2013)

Hyperparameter Selection in Kernel Principal Component Analysis. - Md. Ashad Alam; Kenji Fukumizu (J. Comput. Sci., 2014)

Higher-Order Regularized Kernel Canonical Correlation Analysis. - Md. Ashad Alam; Kenji Fukumizu (Int. J. Pattern Recognit. Artif. Intell., 2015)

Influence Function of Multiple Kernel Canonical Analysis to Identify Outliers in Imaging Genetics Data. - Md. Ashad Alam; Vince D. Calhoun; Yu-Ping Wang 002 (BCB, 2016)

Robust Kernel Canonical Correlation Analysis to Detect Gene-Gene Interaction for Imaging Genetics Data. - Md. Ashad Alam; Osamu Komori; Vince D. Calhoun; Yu-Ping Wang 002 (BCB, 2016)

Learning schizophrenia imaging genetics data via Multiple Kernel Canonical Correlation Analysis. - Owen Richfield; Md. Ashad Alam; Vince D. Calhoun; Yu-Ping Wang 002 (BIBM, 2016)

Gene Shaving using influence function of a kernel method. - Md. Ashad Alam; Mohammad Shahjama; Md. Ferdush Rahman (CoRR, 2018)

Ecological Data Analysis Based on Machine Learning Algorithms. - Md. Siraj-Ud-Doula; Md. Ashad Alam (CoRR, 2018)

Identifying outliers using multiple kernel canonical correlation analysis with application to imaging genetics. - Md. Ashad Alam; Vince D. Calhoun; Yu-Ping Wang 002 (Comput. Stat. Data Anal., 2018)

Influence function and robust variant of kernel canonical correlation analysis. - Md. Ashad Alam; Kenji Fukumizu; Yu-Ping Wang 002 (Neurocomputing, 2018)

Robust kernel canonical correlation analysis to detect gene-gene co-associations: A case study in genetics. - Md. Ashad Alam; Osamu Komori; Hong-Wen Deng; Vince D. Calhoun; Yu-Ping Wang 002 (J. Bioinform. Comput. Biol., 2019)

A generalized kernel machine approach to identify higher-order composite effects in multi-view datasets. - Md. Ashad Alam; Chuan Qiu; Hui Shen 007; Yu-Ping Wang 002; Hong-Wen Deng (CoRR, 2020)

NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning. - Md. Mehedi Hasan 002; Md. Ashad Alam; Watshara Shoombuatong; Hong-Wen Deng; Balachandran Manavalan; Hiroyuki Kurata (Briefings Bioinform., 2021)

A generalized kernel machine approach to identify higher-order composite effects in multi-view datasets, with application to adolescent brain development and osteoporosis. - Md. Ashad Alam; Chuan Qiu; Hui Shen 007; Yu-Ping Wang 002; Hong-Wen Deng (J. Biomed. Informatics, 2021)

IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations. - Md. Mehedi Hasan 002; Md. Ashad Alam; Watshara Shoombuatong; Hiroyuki Kurata (J. Comput. Aided Mol. Des., 2021)

A robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery. - Md. Ashad Alam; Hui Shen 007; Hong-Wen Deng (CoRR, 2022)

Weighted Scaling Approach for Metabolomics Data Analysis. - Biplab Biswas; Nishith Kumar; Md. Aminul Hoque; Md. Ashad Alam (CoRR, 2022)

RoBERTa-BiLSTM: A Context-Aware Hybrid Model for Sentiment Analysis. - Md. Mostafizer Rahman; Ariful Islam Shiplu; Yutaka Watanobe; Md. Ashad Alam (CoRR, 2024)